Multiple Linear Regression Analysis

Description

Performs a multiple linear regression analysis with separate handling of quantitative and binary predictors, including univariate, bivariate, and multivariate results with interpretation categories (a-d). All numeric values stored unrounded.

Usage

linear_reg_answers(
  data,
  criterion,
  quant_predictors = NULL,
  binary_predictors = NULL,
  quant_labels = NULL,
  binary_labels = NULL,
  criterion_label = NULL,
  verbose = FALSE
)

Arguments

data A data frame or tibble.
criterion Character string. Name of the criterion (dependent) variable.
quant_predictors Character vector or NULL. Names of quantitative predictors.
binary_predictors Character vector or NULL. Names of binary predictors.
quant_labels Character vector or NULL. Display labels for quantitative predictors.
binary_labels Character vector or NULL. Display labels for binary predictors.
criterion_label Character string or NULL. Display label for the criterion.
verbose Logical. Print diagnostic information. Default is FALSE.

Value

A list with elements (all numeric values unrounded).

Examples

library("psych350lab")

# Using Superman data: predict rt_critics_score from year and clark_age
result <- linear_reg_answers(
  psych350data::superman,
  criterion = "rt_critics_score",
  quant_predictors = c("year", "clark_age"),
  quant_labels = c("Year", "Clark's Age")
)

# Access model results
result$Model
result$Bivariate
result$Regression_Weights